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Multimodal integration using a machine learning approach facilitates risk stratification in HR+/HER2- breast cancer.

Cell reports. Medicine
Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer is the most common type of breast cancer, with continuous recurrence remaining an important clinical issue. Current relapse predictive models in H...

"Tom and Pepper Lab". Robotics for cognitive stimulation and social skills: A preliminary study.

Asian journal of psychiatry
Dementia affects over 55 million people globally, with early cognitive decline, such as Mild Cognitive Impairment (MCI), often preceding neurodegenerative diseases. This decline impairs memory, attention, and Theory of Mind (ToM). Early intervention ...

Deep Learning-Based Assessment of Lip Symmetry for Patients With Repaired Cleft Lip.

The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
ObjectivePost-surgical lip symmetry assessment is a key indicator of cleft repair success. Traditional methods rely on distances between anatomical landmarks, which are impractical for video analysis and overlook texture and appearance. We propose an...

Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.

Medicina (Kaunas, Lithuania)
: Recent research has focused on exploring the relationships between various factors associated with headaches and understanding their impact on individuals' psychological states. Utilizing statistical methods and machine learning models, these studi...

Automatic Measurement of Frontomaxillary Facial Angle in Fetal Ultrasound Images Using Deep Learning.

Sensors (Basel, Switzerland)
Accurate measurement of frontomaxillary facial (FMF) angles in prenatal ultrasound (US) scans plays a pivotal role in the screening of trisomy 21. Nevertheless, this intricate procedure heavily relies on the proficiency of the ultrasonographer and te...

Robust Automated Harmonization of Heterogeneous Data Through Ensemble Machine Learning: Algorithm Development and Validation Study.

JMIR medical informatics
BACKGROUND: Cohort studies contain rich clinical data across large and diverse patient populations and are a common source of observational data for clinical research. Because large scale cohort studies are both time and resource intensive, one alter...

Results comparison of cervical cancer early detection using cerviray ® with VIA test.

BMC research notes
OBJECTIVES: This study investigates the performance of artificial intelligence (AI) technology, namely Cerviray AI, compared with Cerviray expert, aiming to compare its sensitivity, specificity, positive predictive value (PPV), and area under the rec...

Deep learning-based synthetic CT for dosimetric monitoring of combined conventional radiotherapy and lattice boost in large lung tumors.

Radiation oncology (London, England)
PURPOSE: Conventional radiotherapy (CRT) has limited local control and poses a high risk of severe toxicity in large lung tumors. This study aimed to develop an integrated treatment plan that combines CRT with lattice boost radiotherapy (LRT) and mon...

Death risk prediction model for patients with non-traumatic intracerebral hemorrhage.

BMC medical informatics and decision making
BACKGROUND: This study aimed to assess the risk of death from non-traumatic intracerebral hemorrhage (ICH) using a machine learning model.

Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features.

BMC public health
BACKGROUND: Depressive symptoms in adolescents can significantly affect their daily lives and pose risks to their future development. These symptoms may be linked to various factors experienced during both childhood and adolescence. Machine learning ...